Self-organizing distributed architecture supporting dynamic space expanding and reducing in indoor LBS environment

Area of Science:

• Computer Science
• Ubiquitous Computing
• Network Infrastructure

Background:

• Indoor location-based services (iLBS) face challenges due to dynamic environments and frequent resource requests.
• Traditional centralized map-based iLBS platforms suffer from scalability issues, single points of failure, and poor adaptability.

Purpose of the Study:

• To propose a self-organizing and fully distributed platform for iLBS.
• To address the limitations of centralized approaches in dynamic indoor network environments.

Main Methods:

• Developed a self-organizing distributed platform for iLBS.
• Implemented dynamic reconfiguration of locality accuracy and service coverage.
• Evaluated scalability through simulations involving node insertion/deletion.

Main Results:

• The proposed distributed platform demonstrates enhanced scalability compared to traditional methods.
• The system dynamically reconfigures locality accuracy and service coverage.
• Performance was validated in simulations mimicking real-world dynamic infrastructure.

Conclusions:

• The self-organizing distributed platform offers a scalable and adaptable solution for iLBS.
• This approach effectively manages dynamic network environments and resource lookups.
• The findings support the viability of distributed architectures for future iLBS development.